Indie Rock and Donald Trump

I drive my oldest daughter to high school every day. She goes to a magnet STEM school in the district that’s on the campus where I work. I’ve been brainwashing her into liking indie rock one car ride at a time using carefully planned mix CDs.

Last week she tells me I need to put more Magnetic Fields songs in the mix. Why? I ask.

“Physics homework.” she says.

It turns out that there’s a number of principles of physics that she remembers through a complex set of associations she’s developed referencing indie rock songs. I don’t pretend to get them all, but the 69 Love Songs hit “Meaningless” plays an apparently crucial role.

Later that day, my youngest daughter is asking me about the book Persepolis, a book about growing up Iranian during and after the 1979 Islamic Revolution. The author of that book spends the preface talking about the reasons she wrote it, and how she felt the understanding of her native country of Iran was too narrow, and in a way, too exotic. My daughter tells me that she doesn’t quite get what the author is talking about. After all, there’s a lot of fundamentalism in the early parts of the book — and people really are in a revolution in 1978, so what are we getting wrong in the West?

I know that this daughter, a middle schooler, has had some stress about Donald Trump. She has people in her class who like him, and she can’t understand why when he’s so mean. It worries her.

I ask her if Trump gets elected, how would she feel if everyone assumed all Americans were like Donald Trump. Well, we wouldn’t be, she says.

Oh, she says.

We Have Personalization Backwards

When we talk personalization, we tend to talk about targeting. You learn a certain set of things, you get tested, the personalization software finds knowledge gaps and runs you through the set of canned explanations that you need. (There are other, related meanings, for which Feldstein and Hill provide a partial taxonomy here).

The idea seems to be that there is a wide variety in what concepts students struggle with, but there is one perfect explanation per concept. Personalization gets the explanation of that concept to the student.

That’s part of the story, but it’s not the most important half.

When tutors work with students they certainly alter what they work on based on student need. They personalize what skills they target.

But the biggest advantage of a tutor is not that they personalize the task, it’s that they personalize the explanation. They look into the eyes of the other person and try to understand what material the student has locked in their head that could be leveraged into new understandings. When they see a spark of insight, they head further down that path. When they don’t, they try new routes.

If you find yourself teaching people something — anything — you’ll see this at work. How many times do you being with the phrase “So have you heard of X?” There you are, looking for the way into the explanation. It could be from point X, a Magnetic Fields song. Or from point Y, a Trump analogy. For a Trump-supporting indie-rock-hater it’s going to be a completely different entry point, and a different explanation.

I see little talk about this in the marketing of personalization. Yes, we talk "playlists" and "customized paths", but it’s as if we’re addressing vitamin deficiencies. The assumption is that everyone is deficient in different ways, but given any individual’s deficiency there is one remedy. You’re uniquely deficient in folate and iron; here’s the standard five milligrams of folic acid and an iron supplement. In a personal playlist!

While not entirely useless, this conception doesn’t fit the bulk of my experience as either a teacher or a learner. In my experience, students often have very similar skill gaps, but the remedy for each student may be radically different.

A truly personalized system would not merely find the questions the student needs explanations for: it would find the explanations most useful to the students. And by most useful, I don’t mean “learning styles” or “friendly robots in the sky” or anything like that. I mean keying into the fact that an adult student who is struggling in Introductory Psychology might in fact be an expert in business negotiation, and finding an explanation of “confirmation bias” that makes use of that student’s existing knowledge and talents rather than treating it as irrelevant.

I mean giving some students that have access to a lot of vocabulary that can help them grasp new concepts quickly one explanation, while giving other students less concise explanations that avoid specialized vocabulary for the moment. At some level, I mean that the kid who loves indie rock will find the indie rock inflected explanation of something when it's out there.

I'm not talking about a system that stores three publisher produced versions (image-based! textual! kinesthetic!) of content directed to students on the basis of a multiple choice test. I'm talking about something much more radical than that, a system that has hundreds of explanations and examples for any concept the student wishes to learn.

What Real Personalization Would Look Like

With the right system of connected explanations and examples we could serve students the individual content they need on numerous dimensions:

The"traditional" student could get the explanation that taps into dorm life and high school drama, while the older student could get an example that resonates more with their life and doesn't make them feel unwelcome every time they read the textbook.

Students who find one example too difficult could "dial-down" to something more introductory.

Students with a special area of expertise would have opportunities to leverage that expertise to understand new things.

Students with accessibility issues could get accessible content, and rather than universal design meaning the best possible path for everybody it could mean the material and platform out of which anyone could construct a viable and unique path, regardless of strengths and challenges.

As students came to understand things, they would write their own explanations and examples which could be fed back into the system to be used by others.

If we in the OER community were pursuing this dream, here's some things we'd be working on:

Modular content instead of textbooks. Tons of the stuff.

Massively varied content instead massively generic content.

Recommendation engines that track what sort of content works for individual people.

Technology that allows individual students to share and curate the material that works for them.

Systems for students and faculty to create, fork, and improve content they use.

Personalization technologies that map the thin content of textbooks and courseware to testable student needs.

I understand why this is (I really do!). We have to pave the existing cowpaths, to some extent, and that means content swapped in at the level of the course, not the individualized need. The fact we are even at the table suggesting open substitutes is the result of a decade and a half of focused effort. I get it.

But as we build these linear, centralized systems, the rest of the world is moving beyond them. It's time we take notice and build the kind of learning environment that open resources might make uniquely possible.

***

On today's indie rock car ride my daughter mentions she has to write a piece for her college history course relating Churchill's Iron Curtain speech to the ensuing Cold War. She absolutely hates history (which kills a history lover like me, but there you go). She's an engineering geek, an astronomy nut who loves to tell you the physics of how the first probe got to Mars, but couldn't distinguish John Adams from Thomas Jefferson.

So an essay about the Iron Curtain? Ugh.

Well, I venture, one thing to remember about that speech is that the Soviets were really frightening at the time. They were a technologically advanced society that seemed willing sacrifice anything for the national interest. It scared the bejeezus out of us.

"Tell me about it," she says. And then she launches into this detailed story of how the Americans were in awe of the early Soviet space program, and couldn't figure out how they were doing this stuff. But the thing about the Soviets was they would never announce a mission until it was successful, so they could fail multiple times where the Americans couldn't. And even with small things they would control the narrative. Laika, the famous dog the Russians sent into space, died a brutal death in the first hours of her flight and was never meant to be retrieved, but the full story of that flight wasn't known until the 2000s. Even the Russian focus on Venus vs. Mars was interesting, in that failure on Venus was much less public.

Huh, I say. You think you could relate some of that to the Iron Curtain speech?

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Comments

Richard and Daniel Susskind have written an interesting book, The Future of the Professions. One of the key points is to refute the argument that the personalized nature of the professions, and here, we include education, makes the phrase, not in my profession, true when looking at disruptive technologies. As the Susskinds note, if the practice can be deconstructed, much can be managed by technology and much can be handle by humans, but transformed in theory and practice.

One is reminded of the 60’s program, the Rogerian analyst, Eliza. And, today, while Knewton may seem, as described here, to support the professions’ argument, Google, Amazon, Facebook and many other “Deep Learning”, Big Database, systems point out their razor fine understanding of individuals and the collective. Combined with the work on Robot/human interfaces, it seems to belie the argument. Kevin Kelly’s soon to be released volume, The Inevitable, reinforces this as society shifts. The ability of these AI systems to simultaneously function in multiple languages and to add large numbers of individuals as individuals does not require one to evoke such SF writings as Stephenson’s The Diamond Age.

One could very easily construct the father/daughter exchange as a discussion between the students and an intelligent AI engine. Again, the very primitive Eliza and other examples from behavioral science bring fiction into practice.

The discussion of OER’s current path points out that we are still grasping for immediate solutions to today’s concerns, but not at the expense of the education professional; for if one looks at the various other proposals for student learning, all tend to avoid a discussion of the possibility of a disruptive “moment” for the professionals as possibilities move past the peak of the “hype cycle”, whether K-12 or beyond.

Maybe it’s time to look at the professionals who seem to be harboring some Luddite tendencies which run straight up to the schools of education and the faculties,particularly with the shift from tenure track to adjuncts in the “classroom”. Perhaps the disruption being resisted is at that level?

[…] With the right system of connected explanations and examples we could serve students the individual content they need on numerous dimensions:The”traditional” student could get the explanation that taps into dorm life and high school drama, while the older student could get an example that resonates more with their life and doesn’t make them feel unwelcome every time they read the textbook.Students who find one example too difficult could “dial-down” to something more introductory.Students with a special area of expertise would have opportunities to leverage that expertise to understand new things.Students with accessibility issues could get accessible content, and rather than universal design meaning the best possible path for everybody it could mean the material and platform out of which anyone could construct a viable and unique path, regardless of strengths and challenges.As students came to understand things, they would write their own explanations and examples which could be fed back into the system to be used by others. If we in the OER community were pursuing this dream, here’s some things we’d be working on:Modular content instead of textbooks. Tons of the stuff.Massively varied content instead massively generic content.Recommendation engines that track what sort of content works for individual people.Technology that allows individual students to share and curate the material that works for them.Systems for students and faculty to create, fork, and improve content they use.Pedagogy that allows multiple approaches to (and ultimately multiple interpretations of) course goals. Now, here’s what we seem to be working on instead:Textbooks (but open).End-to-end courseware (but free).Personalization technologies that map the thin content of textbooks and courseware to testable student needs. […]

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